I am trying to visualize the gene expression difference between different samples. I am using edgeR to analyze rna-seq data. I have done PCA and MDS plots on the samples and the samples separate nicely into groups between treatments and time points. Now I would like to see how the genes separate on the same plot between samples. I would for example like to see if genes cluster with certain samples. I manage to create the PC plot with the help of prcomp() and use ggplot to visualize the data.
Someone knows how I can do this?

I didn't understand what you're trying to achieve. Samples are plotted using vectors of values which in this case is gene expression level. Genes can be reduced in the same way to 2D (which is what PCA does) using the samples as the vector of values. Are you trying to plot both PCAs on the same grid?

Thank you for the answer, and if I am not that precise in my explanation, that is because I am a beginner in analyzing RNA-seq data. As I understand it the PCA data from prcomp() have the positions of the samples and also the vector directions of the genes. I have tried printing a biplot with both values. I want to see if I can explain the separation between the samples to specific genes and show it by for example printing all genes and the genes that goes to one axis cluster to one sample and the other sample has other gene clustered to them.

I can color the points to each sample if they have different timepoints and so on by adding different designs. But I don't know how I would do that to different genes which are expressed by several samples.

No I have not corrected for batch effect. I have 4 biological replicates which I guess could be corrected, because they cluster slightly more than other parameters. The groups I am talking about is for example all samples at one timepoint cluster in one area and the other timepoint in the other.